Machine Learning Reports

Ground Penetrating Radar (GPR) is considered as one of the promising technologies to address the challenges of detecting buried threat objects, particularly in military ap-plications. The aim of this research is to design a potential solution to the task of target detection and classification using GPR. This paper focuses on the first stage of this task which is target detection. Three approaches for automated target detection are presented; a probabilistic approach, an artificial neural network with direct data input, and an artificial neural network with frequency spaced features. These techniques are applied to a preliminary data set with promising results.